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| Bayesijanska analiza dvomodnih mreža× | Težinska analiza dvomodnih mreža× | |
|---|---|---|
| Područje | Analiza mreža | Analiza mreža |
| Obitelj | Machine learning | Machine learning |
| Godina nastanka≠ | 1997–2010s | 1997 (two-mode); weighted extensions 2000s |
| Tvorac≠ | Borgatti & Everett (two-mode SNA); Bayesian extensions by multiple authors | Borgatti, S. P. & Everett, M. G. |
| Vrsta≠ | Probabilistic network model | Network structural analysis |
| Temeljni izvor | Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269. DOI ↗ | Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269. DOI ↗ |
| Drugi nazivi | Bayesian bipartite network analysis, probabilistic two-mode network analysis, Bayesian affiliation network analysis, Bayesian two-mode SNA | weighted bipartite network analysis, valued two-mode network analysis, weighted affiliation network analysis, W2MNA |
| Srodne≠ | 5 | 6 |
| Sažetak≠ | Bayesian two-mode network analysis applies probabilistic Bayesian inference to bipartite (two-mode) networks — graphs linking two distinct sets of nodes such as actors and events, authors and papers, or consumers and products. By placing priors over tie probabilities and structural parameters, analysts obtain uncertainty estimates around centrality, community membership, and projection metrics rather than single-point estimates. | Weighted two-mode network analysis examines bipartite graphs in which two distinct node sets — such as actors and events, authors and papers, or species and habitats — are connected by edges carrying numerical weights that capture the strength, frequency, or intensity of each affiliation. Incorporating weights provides substantially richer structural insights than unweighted bipartite analysis. |
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